Neural networks are distributed computing structures inspired by the structure of a biological brain and aim to achieve cognitive performance comparable to that of humans but in a much shorter time.

Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and ...

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research published in APL Machine Learning, I have used a phenomenon ...

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...

Physics-informed neural networks are faster and more accurate at predicting space junk trajectories than conventional methods, says Sierra Space. Credit: Alamy Stock Photo Sierra Space says it can ...

A deep neural network was trained using quantum tunneling to mimic the human ability to view optical illusions. When you purchase through links on our site, we may earn an affiliate commission. Here’s ...

Biology-inspired, silicon-based computing may boost AI efficiency; AMP2 instead uses AI to accelerate anaerobic biology.

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Scientists have developed an entirely new kind of microchip that uses microwaves instead of conventional digital circuitry to perform operations. The processor, which can perform faster than ...